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Environmental and economic impact assessment of construction and demolition waste disposal using system dynamics
Resources, Conservation and Recycling 82 (2014) 41–49
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Resources, Conservation and Recycling journal homepage: www.elsevier.com/locate/resconrec
Environmental and economic impact assessment of construction and demolition waste disposal using system dynamics Mohamed Marzouk ∗ , Shimaa Azab Structural Engineering Department, Faculty of Engineering, Cairo University, Egypt
a r t i c l e
i n f o
Article history: Received 1 March 2013 Received in revised form 8 September 2013 Accepted 27 October 2013 Keywords: Construction and demolition wastes (CDW) Environmental and economic impact assessment Pollutant emissions Waste recycling Global warming potential (GWP) System dynamics modeling
a b s t r a c t Construction and demolition wastes (CDW) have increasingly serious problems in environmental, social, and economic realms. There is no coherent framework for utilization of these wastes which are disposed both legally and illegally. This harms the environment, contributes to the increase of energy consumption, and depletes finite landfills resources. The aim of this paper is to evaluate the impacts of two alternatives for the management of CDW, recycling and disposing. The evaluation is carried out through developing a dynamic model with aid STELLA software by conducting the following steps: (1) quantifying the total cost incurred to mitigate the impacts of CDW landfills and uncollected waste on the environment and human health; (2) quantifying the total avoided emissions and saved energy by recycling waste; (3) estimating total external cost saved by recycling waste and; (4) providing a decision support tool that helps in re-thinking about waste disposal. The proposed evaluation methodology allows activating the stringent regulations that restrict waste disposal and developing incentives to encourage constructors to recycle their wastes. The research findings show that recycling CDW leads to significant reductions in emissions, energy use, global warming potential (GWP), and conserves landfills space when compared to disposal of wastes in landfills. Furthermore, the cost of mitigating the impact of disposal is extremely high. Therefore, it is necessary to recycle construction and demolition wastes. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The construction/demolition industry is considered one of the largest producers of solid wastes globally. The huge amount of construction and demolition wastes (CDW) has been generated from increasing the building of new structures, renovation, rebuilding, repair, demolition works, and infrastructure development projects. Large quantities of construction and demolition wastes (CDW) cause harmful effects on the environment if they are not managed in proper manner. As such, these huge amounts of wastes need to be properly managed. The current situation of waste management in Egypt lies in disposed waste either legally or illegally and there is no coherent framework for making the most of these wastes. It is very important to give priority to the environment in addition to conventional project objectives, such as cost, duration, quality and safety (Liyin et al., 2006). Thinking about waste management from a limited perspective gives rise to some economic concerns. This is because a large amount of money is spent on dumping the waste in landfills and mitigating the effects of dumping on the environment. The environmental problems include: (1) diminishing landfill space due to incremental quantities of these disposed wastes in it; (2) the
∗ Corresponding author. Tel.: +202 35678442. E-mail address: mm [email protected] (M. Marzouk). 0921-3449/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.resconrec.2013.10.015
depleted building materials; (3) the increase in contamination from landfills that lead to serious negative health effects; (4) damage to the environment; and (5) the increase in energy consumption for transportation and manufacturing new materials instead of those materials dumped and which require energy production. The later problem is attributed to the loss of embodied energy of the disposed wastes that can be used to produce new construction materials. It is worth noting that CDW recycling saves the embodied energy in waste materials by the replacement of virgin raw materials with recycled materials (Roussat et al., 2009). Therefore, energy savings are often the driving force behind emissions savings (Choate et al., 2005). CDW are adding to the phenomenon of global warming. Hotter temperatures due to Global Warming Potential (GWP) lead to increased weather extremes including heat waves and worsening of air quality. Epidemiological studies of deaths during the heat waves refer to the fact that a substantial portion of the mortality might be attributed to elevated ozone and particulate levels that occurred during the heat waves (American lung Association, 2004). The California Air Resources Board indicated that the health effects of increasing concentrations of particulate matter and ozone are: 6500 premature deaths, 4000 hospital admissions for respiratory disease, 3000 hospital admissions for cardiovascular disease, 350,000 asthma attacks, 2000 asthma-related emergency room visits, elevated school absences due to respiratory conditions,
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including asthma, and reduced lung function growth rate in children. Sensitive groups, including seniors, people with heart or lung disease, children and infants are the most vulnerable to the harmful effects of air pollution. On the other hand, CDW recycling technique has recently attracted the attention of many researchers due to its economic and environmental benefits. In economic terms, plenty of studies have been conducted on the economic situation of CDW recycling plants such as (Coelho and de Brito, 2013a; Zhao et al., 2010). Both of these studies confirmed the economic feasibility of recycling CDW, but with different results due to the conditions of each study. Coelho and de Brito (2013a) conducted a study on a large-scale recycling plant in Portugal to evaluate the economic viability of the plant for serving a densely populated urban area. This study concluded that despite the absence of regulatory government policy the initial investment required for recycling may be high, but there is a high profit potential for CDW recycling with the return of invested capital in around two years. Zhao et al. (2010) developed a study of the situation in Chongqing in China to assess the economic viability of the implementation of fixed recycling CDW plant facilities and mobile recycling stations and compared it with recycling centers (mobile stations) in the Netherlands to find out successful factors for recycling centers. This study has concluded that fixed and mobile recycling centers with used equipment have higher economy viability than centers with new equipment and that is due to their ability to achieve a higher profit margin in contrast to the second case. Also, the revenue increases owing to the location advantage (e.g. mobile stations) and the recycling cost decreases with the economy of scale (e.g. fixed centers). This study has also suggested the use of economic and political instruments to face the investment risks. Regarding the environmental concerns from recycling plants, several studies have been conducted to evaluate the environmental impacts from CDW recycling plants. Coelho and de Brito (2013b) conducted a study using life cycle assessment of CDW recycling plant with a capacity of 350 ton/h and 60-year operating lifespan. This study has focused on the evaluation of two impacts of recycling plant, namely the primary energy consumption and CO2 eq emissions. The main conclusion of this study is that recycled materials always have significant environmental benefits where the avoided impacts of CO2 eq emissions are always higher than the generated impacts and energy savings exceed the energy consumed during the operating lifespan. F.I.R. (2005) pointed out for several studies conducted to assess the environmental impacts from recycling building materials using life cycle assessment approach from extraction to recovery or disposal of landfills. The first study is presented for assessing the greenhouse gases generated from primary and recycled aggregate. The study has concluded that the recycled aggregate was more environmentally useful than most of primary aggregate. The second study is presented for evaluating environmental impacts of production of 1 ton of concrete through comparing two different scenarios, which are landfilling and recycling. According to this study, the second scenario (recycling) is more environmentally friendly. In order to overcome the above-listed growing problems caused by CDW disposal, it is important to consider a recycling solution. Recycling allows utilizing wastes as raw materials in some other ways. This paper proposes the use of system dynamics methodology to compare between two alternatives of CDW management techniques; recycling and landfill disposal. This model is capable of: (1) measuring the total emissions from the CDW landfilling and associated costs incurred to mitigate the impacts from these emissions; (2) predicting the total damage costs of disposed waste and from uncollected wastes; and (3) quantifying the total avoided emissions and the energy saved by waste recycling. The novelty of this research lies in adopting a system dynamics
approach for all basic variables underlying the evaluation of the two alternatives during the lifetime of landfills. It outperforms previous studies which focus on assessing the two alternatives without taking into account the dynamic nature and relationships between variables. Plenty of studies have been carried out to model CDW management using system dynamics, but they did not take into account the dynamic nature of the CDW disposal and interactions among major variables affecting on evaluation of economic and environmental effects of the CDW disposal as two important aspects of sustainability. This research is an attempt to provide the stakeholders of Egyptian construction sector with an empirical study that considers all variables that influence the CDW. Also, this study helps in mitigating the risks associated with CDW disposal and illustrates the benefits of recycling of construction wastes. 2. Theory and calculations System dynamics is an approach for studying and managing complex feedback systems and is specially created to deal with large-scale and complex systems (Yuan et al., 2012). A system is a group of interacting or interdependent entities forming an integrated whole system dynamics modeling (Cheng, 2012). It was originated by Professor Jay W. Forrester of the Massachusetts Institute of Technology during the mid-1950s (Forrester, 1987). It has been widely used in different applications for understanding different economic, social, business, agricultural, and ecological systems. It deals with internal feedback loops and time delay that affect the behavior of the entire system. It has the ability to understand the relation between the behavior of system over time and its underlying structure and decision rule. Simulation helps explore “what-if” scenarios and policy tests in something that is like a laboratory setting, which causes confidence in particular strategies and policies to increase (Richardson and Otto, 2008). As a result, “system dynamics is often used as a methodology for improving the soundness and effectiveness of the decision-making process. It has become a popular technique for modeling construction project management” (Hao et al., 2007). 3. System dynamics applications in CDW A big number of research works have utilized system dynamics modeling in waste management. Wager and Hilty (2002) have developed system dynamics model for waste management to support the assessment of the flow of materials, energy and costs of regional waste management with regard to their ecological and economic impacts. Chaerul et al. (2008) studied hospital waste management using system dynamics approach to capture its dynamic nature. The behavior of the waste management system depends on several factors including the changing nature of various systemic factors and the feedback generated by a dynamic and continuous interaction. Sliwa (1994) conducted a study on municipal solid waste management in Pueblo using the system dynamics approach. The study has tried to bridge the gap between traditional approaches so as to solve the public administration problems. Lang et al. (2002) developed a systematic methodology for natural and human resources optimization for waste management to achieve sustainable development using system dynamics modeling. Several studies have been published for CDW management (Yuan, 2012; Hao et al., 2007; Rong, 2004; Hsiao et al., 2002; Zhao et al., 2011; Yuan et al., 2011). Yuan (2012) carried out a quantitative study to evaluate the social performance on construction waste management using system dynamics. Many indicators have been used to assess the social impacts of CDW. Hao et al.
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4.1. Problem identification 1) Problem Identification
5) Policy Formulation
4) Model Validation
2) Dynamic Hypothesis
3) Model formulation
Fig. 1. System dynamics model procedure for CDW.
(2007) conducted a study on managing construction and demolition waste. The study showed that system dynamics is able to interrelate the sub-systems and provide better understanding of the dynamic interactions and interdependencies of the key areas of the CDW management process. Rong (2004) used system dynamics approach and analytical hierarchy processing an effort to model sustainable waste management techniques. Hsiao et al. (2002) conducted a study on simulating materials flow of concrete waste from construction and demolition wastes. Also, Zhao et al. (2011) developed a study using system dynamics computer model to evaluate alternatives in CDW recycling centers under different policy and economic environments. Yuan et al. (2011) developed system dynamics model for analyzing the cost-benefit for CDW management. An economic instrument is developed as an effective tool for encouraging or forcing contractors to conduct environmentally friendly construction practices. Previous studies did not take into account the need for assessment of economic and environmental effects of CDW disposal as two important aspects of sustainability. Also, they did not model the different pollutant emissions resulting from disposal in landfills throughout their lifetime from a dynamic point of view. To simulate a system dynamics model, computer support is needed. There are several existing computer packages such as DYNAMO, IThink/STELLA, Matlab, Powersim and Vensim. STELLA is one of the most popular system dynamics software packages which are an effective simulation tool for system dynamics modeling released by High Performance Systems Inc. (HPS, 1997). This software was selected for supporting the analysis in this study. The basic building blocks of STELLA are stock; flow; converter; and connector. A stock variable (represented by rectangles) is a noun and represents something that accumulates. A flow (represented by valves) is an activity that changes the magnitude of a stock by filling and draining. The converter (represented by circle) can be used to modify an activity for its ability to define external inputs to the model. The connector (represented by simple arrow) is able to connect model elements (Shiflet and Shiflet, 2006; Zhao et al., 2011). 4. Development of system dynamics model The objective of this research is to provide a dynamic model by conducting an empirical study using system dynamics methodology to capture the dynamic nature of two alternatives for CDW management which are waste recycling and disposal. The proposed model is able to simulate the long-term behavior of each alternative in two main aspects of cost and environmental impacts. To achieve this objective, a simulation model is developed by following the procedure shown in Fig. 1. The description of the proposed procedure is detailed in below sub-sections.
To simulate the long-term impacts of CDW recycling and landfilling on the aspects of cost and environment, all essential variables that affect the system are considered. The variables rates used in the model have been collected from various published literature and through surveying the Egyptian market. The time horizon should be long enough to show the impact of CDW recycling and disposal and describe its symptoms. Therefore, it should extend far back in history. Also, it should extend far enough into the future to capture the delayed and indirect effect of potential policies (Sterman 2000). Rong (2004) recommended the service life of the waste treatment/disposal facility that is usually 20–30 years. Therefore, the time horizon in the proposed system dynamics model is selected to be 20 years (i.e., from 2004 to 2024).
4.2. Dynamic hypothesis Evaluating economic and environmental impacts of CDW management alternatives on the long-run requires examining the major variables effect on the assessment. This is done by using a tool that is capable of visualizing relationships of variables and feedback effects of the system. The structure of the system dynamics model is portrayed by a causal loop diagram, which is formulated by VENSIM software as shown in Fig. 2. The developed causal loop diagram comprises eight loops (R1, R2, R3, R4, R5, R6, R7, and R8) in total; all loops are reinforcing (positive loops). The interactions among different loops decide the system’s final behavior. Feedback loop R1 shows the relationship between CDW recycling and energy consumption saving where CDW recycling leads to an increase in energy consumption savings. On the other hand, when savings in energy consumption from recycling increase, it leads to conduct more recycling. This relationship, as a natural result of the recycling process, reduces the need for the upstream phase. When using recycled materials, this replaces part of the inputs that would be produced from raw material, skipping some stages of the production chain or replaces some stages which lead to less energy-consumption (Pimenteira et al., 2004). Feedback loop R2 shows that the recycling process helps in reducing emissions polluting the air ambient (e.g. NOX, SO2, PM, and CO emissions) which leads to better human health. As a result, all emissions polluting the air will be reduced when more recycling takes place instead of landfilling, where the total reductions in emissions is equal to the avoided emissions from landfilling plus the avoided emissions from reducing the need for the upstream phase. Energy savings are often the driving force behind emissions savings (Choate et al., 2005). Consequently, the amount of recycled waste will be increased due to the total reduction in pollutants emissions. By referring to feedback loop R3, it can be observed that the amount of greenhouse gases (GHGs) emissions is reduced by increasing recycling. This in turn leads to reducing the chance of causing global warming potential. Consequently, the amount of recycled waste will be increased due to the reduction in the GWP phenomenon. The causal loop relationships in loop 4 are the same as in loop R2; the only difference is the effect of GHGs emissions instead of emissions polluting the air. Some of the causal loop relationships in loop R5 are the same as in loop R4; the difference is that the total reduction in emissions from landfills leads to an increase in the total saved damage cost through mitigating the effect of these emissions on environment, air ambient, as well as they eliminate the negative effect on human health. This has positive effects on economic gains. Consequently, if economic gains are high, then, contractors are keen to have incentives of having more recycling (Yuan et al., 2011). Economic instrument is perceived as
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Waste Generation Per Capita
Percentage of C&D Waste that Not Collected
+ -
+ Waste Collection + + Uncollected waste + Population Census
+ + C&D Waste Generation
Occupation Of Landfill Space +
+ Waste Disposal +
Existing landfill capacity
Emissions polluting the air
+ Extra Funds for New Landfills
Total Damage Costs From Emissions of Landfills + +
Energy consumption saving + + Greenhouse gas emissions -
Unit landfill Charge
+
-Total Reductions in Emissions By Recycling
+
R1 R3
Population Growth Rate
+ Damage Costs Of Emissions +
R4
+ Recycling Ratio Unit Environmental cost due to uncollected waste
Private Costs Of Unit Landfills
Collection Rate
+
+
Global warming
R2
+
+
R5
+ ECONOMIC GAINS
+
R6
Waste Recycling
-
+
R8
+
+
Total Cost from disposal & uncollected waste R7
+
Unit Damage Cost Of Air Emissions
Total damage cost Avoided By Recycling
Damage Costs from GHG Emissions +
+ + Environmental Cost due to Uncollected Waste
Unit Damage Cost of GHG Emissions.
Fig. 2. Causal loop structure of the proposed model.
an effective tool for encouraging or forcing contractors to adopt environmentally friendly construction practices. Some of the causal loop relationships in loop 6 are the same as in loop R5; the only difference is the effect of emissions polluting the air, not the effect of GHGs emissions. In feedback loop R7; it can be observed that conducting more recycling for CWD leads to the reduction of the emissions polluting the air. The total damage costs from emissions of landfills are consequently reduced since CDW in landfill is less. Also, the total costs from disposal and uncollected waste are reduced. As a result, the economic gains will be increased by conducting more recycling and high economic gains will lead to further recycling. Feedback loop R8 is the same loop R7 except that the effect of emissions polluting the air is replaced by the effect of GHGs emissions. 4.3. Model formulation Based on the causal loop diagram, all the key variables that affect the choice of CDW management techniques alternatives are identified. The conceptual causal loop diagram is converted to a quantitative model to facilitate the running of the model. To this end, the causal loop diagram is converted into a stock-flow diagram using STELLA software. Fig. 3 depicts stock-flow diagram of the model. Detailed descriptions of the model variables are included in Appendix 1. 4.4. Model validation Building confidence in the model is achieved through conducting some tests after identifying and defining all variables and functions (Sterman 2000). This ensures the accuracy of the model for reflecting the real-world in a meaningful way (Richardson and Pugh, 1981). Qudrat-Ullah and Seong (2010) listed five tests that are used for structural validation of a system dynamics model. The
validation tests are conducted in the developed model as described below. 4.4.1. Boundary-adequacy test This test is concerned with whether the level of detailed variables contained in the model is appropriate to the research purpose or not. Meanwhile, it assures that the model includes all relevant structure relationships and parameters by examining all the variables that have been embodied in stock-flow diagram. After examining all variables in the system dynamics model, it was found that each of these variables is fundamental for research purpose so as to evaluate the environmental and economic performances associated with the disposal and recycle of CDW. 4.4.2. Structure verification test The purpose of this test is to check whether the model structure is consistent with relevant descriptive knowledge of the system being modeled. The structural verification is important in the overall validation process (Qudrat-Ullah and Seong, 2010). The information included in the structure and all cause-and-effect chains of the causal loop diagram (shown in Fig. 2) is based on various literatures in this domain. As such, the structure of that model is logical and closely represent the real life system. 4.4.3. Dimension consistency test This test ensures the consistency of variable dimensions of each mathematical equation in the model. STELLA software has the possibility of dimension checking after defining the measurement units of all the variables. Consequently, the model has been validated for dimensional consistency. The variable “AAPMERE” (shown in Fig. 4), for instance, is defined using Eq. (1): AAPMERE (t) = AAPMERE (t − dt) + (APMERE) ∗ dt
(1)
This equation is used to calculate the total avoided PM Emissions through construction and demolition waste recycling. It is
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Fig. 3. A stock-flow diagram for assessing the economic and environmental impacts of CDW.
Equ
AAPMERE (t)
=
AAPMERE (t - dt)
+
Dim
Ton
=
Ton
+
(APMERE) * dt
Ton* Ton/Ton
Fig. 4. Dimension consistency test on one of the model variables.
Table 1 Population growth rate in Egypt 2000–2025 (Awad and Zohary, 2005). Period
2000–2005
2005–2010
2010–2015
2015–2020
2020–2025
Population growth rate (%)
1.91
1.83
1.67
1.46
1.28
worth noting that the variable dimensions on the left-hand side are consistent with the variables dimensions on the right-hand side. 4.4.4. Parameter verification test The purpose of this test is to check whether the parameters in the model correspond conceptually and numerically to real life. The parameter values of the proposed model are taken from real cases conducted in literature. For illustration, Tables 1 and 2 include some of the parameters, their values and the source. 4.4.5. Extreme conditions test This test examines the behavior of the model by assigning extreme values for the model variables. Extreme values for specific variables are compared with the reference behavior of the principled model. To clarify the purpose of the test, the variable ULC (Unit Landfilling Charge) is taken as an example for the test. The impact of ULC on REW (the quantity of recycled from CDW) over time is examined by changing the value of ULC from L.E. 6.11 ($0.88) to L.E. 58 ($8.32) and monitoring how the value of REW influences model behavior. The findings show that in case of higher landfill charge,
contractors’ incentive increases to conduct more CDW recycling which increases REW compared to the initial value of ULC (see Fig. 5a). In case of low unit landfill charge (L.E.6.11), most wastes are disposed either legally or illegally. This result reflects the natural attitude of contractors, where costs represent high priority with the absence of incentives for recycling and/or contract clauses that force contractors to recycle CDW. Table 2 Model variables and their respective values. Model variables
Values
Source
NOX emissions from recycling 1 ton from CDW GWP (CO2 eq) emissions from recycling 1 ton from CDW Energy used for recycling 1 ton from CDW GWP emissions from processing 1 ton of CDW in a Landfill Energy used for Processing 1 ton of CDW in a landfill Unit land losses from landfills space by CDW landfilling
−2 ton −600 Ibs
Levis (2008)
−9000 kBtu 200 Ibs 600 kBtu 0.6 M3 /ton
F.I.R. (2005)
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M. Marzouk, S. Azab / Resources, Conservation and Recycling 82 (2014) 41–49 4.50E+07
5.00E+07
4.00E+07
Unit Landfilling Charge (ULC)=6.11
4.50E+07
3.50E+07
Unit Landfilling Charge (ULC)=58
4.00E+07 3.50E+07
Tons
3.00E+07
Tons
2.50E+07 2.00E+07
2.50E+07
1.50E+07
1.00E+07
1.00E+07
5.00E+06
5.00E+06 0.00E+00
0.00E+00 0
1
2
3
4
5
6
7
8
0
9 10 11 12 13 14 15 16 17 18 19 20
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
Years
b) Quantities of recycled, landfilled and uncollected CDW over simulation time
a) Unit landfilling charge impact on the quantity of recycled from CDW
4.50E+07
3.50E+07 3.00E+07 2.50E+07 2.00E+07 1.50E+07 1.00E+07 5.00E+06
2.00E+12 Kilo Brish Thermal Units (KBTU)
Released GHGs Emissions from Landfills for the same quanty of waste recycled (RGHGELF) Overall Avoided GHGs Emissions by CDW Recycling (OAGHGER)
4.00E+07
Tons CO2eq
3.00E+07
2.00E+07
1.50E+07
-5.00E+06
Recycled CDW (REW) Disposed CDW in Landfill (DWLF) Uncollected CDW (UCOW)
1.80E+12
Saved Energy from Avoiding Landfilling (SEALF)
1.60E+12
Overall Saved Energy by Recycling (OSERE)
1.40E+12 1.20E+12 1.00E+12 8.00E+11 6.00E+11 4.00E+11 2.00E+11 0.00E+00
0.00E+00 0
1
2
3
4
5
6
7
8
0
9 10 11 12 13 14 15 16 17 18 19 20
1
2
3
4
5
6
7
Years d)
c) Effect of recycling and landfills on global warming potential
ed Waste (TCMDDUCOW)
3.50E+12
9 10 11 12 13 14 15 16 17 18 19 20
Amount of Consumed Energy and Saved Energy over simulation time
1.20E+14
Total Costs incurred to Migate the Damage from Disposal and Uncollect
3.00E+12
8
Years
Total Benefits of CDW Recycling (TBRE)
1.00E+14
2.50E+12
8.00E+13
L.E.
L.E.
2.00E+12 1.50E+12
6.00E+13 4.00E+13
1.00E+12
2.00E+13
5.00E+11 0.00E+00
0.00E+00 0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
e) Economic burden from waste disposal over simulation time
f) Economic benefits of waste recycling
Fig. 5. System dynamics model outputs.
5. Results and discussion After conducting the validation tests, the model is simulated over a total period of 20 years, which corresponds to the total life time of CDW landfills. In case of enforcement methodology to benefit from construction and demolition waste by recycling instead of disposal (without implementing government policies), the proportion of recycled materials is influenced by contractors’ perceptions where cost has higher priority than environment. Thus, the percentage of recycled material is influenced by the unit landfill charge. Fig. 5b depicts the projection of the amount of CDW that is: (1) disposed in landfills; (2) uncollected; and (3) recycled. It should be noted that the amount of waste recycled (REW) in the first year is only 20% of the total collected waste that is approximately 32 thousand ton and over the simulated time (20 years). A total of 12.3 million ton of materials will be recycled from a huge amount of CDW that is generated annually (4.5 million tons/year). This quantity is considered very little compared to the quantities dumped in landfills annually and uncollected wastes. The total disposed waste in landfills (DWLF) over a lifetime is 49.2 million
ton and this represents the largest amount of waste, which leads to diminishing landfill space rapidly and causes ambient air pollution that is so dangerous to human health. The amount of uncollected wastes (UCOW) is 35.2 million ton over a simulation time which is much greater than the amount of recycled wastes. This is attributed to the absence of enforcing strict laws and regulations that prevent illegal dumping for the preservation the environment. Fig. 5c depicts the comparison between the simulation of the effect of GHGs emissions released from landfills and the impact of the recycling process on global warming potential (GWP). The figure shows the effect of disposed waste on GWP through the amount of GHGs emissions (CO2 eq) released from landfills (RGHGELF) and the effect of the recycling process by estimating the overall avoided GHGs emissions by CDW Recycling (OAGHGER) that is equal to the total avoided emissions from landfilling and the avoided emissions from eliminating the need for the upstream phase. It should be noted that GHGs emissions (CO2 eq) released from landfills increases significantly during its operations and even after closure. This leads to an increase in GWP which increases
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emissions in the atmosphere from 228.52 ton in the first run on simulation to 10.45 million ton over 20 years. In contrast, in waste recycling processes, the concentration of GHGs emissions gradually decreases (avoided emissions increase) over time and this leads to a reduction in the chance of global warming from 914 ton in first year of simulation to 41.8 million ton at the end of simulation (2024). Fig. 5d shows the effect of disposed waste in landfills and recycling process in energy consumption. The relationship between SEALF (Saved Energy from Avoiding LandFills) and the lifetime of landfills is depicted in the figure. It shows that the energy consumption by landfilling for the same recycled quantity ranges from 1.37 million KBTU (Kilo British Thermal Units) to 62.69 billion KBTU at the end of the simulation run. These huge losses from energy consumption can be maintained by conducting a recycling process on CDW. The results from simulation indicate that by conducting recycling on the same quantity, OSERE (Overall Saved Energy due to Recycling) ranges from 21.94 million KBTU to 1003 billion KBTU. It is a fact that recycling reduces the need for the upstream phase. Also, when materials are recycled, this replaces part of the inputs that would be produced from raw material, skipping some stages of the production chain or replacing some stages which lead to less energy-consumption. Fig. 5e depicts the impact of not handling the CDW in an appropriate manner on the economy. A large amount of money will be incurred by the government to: (1) eliminate the damage that results from landfills emissions whether in air ambient or on human health; (2) reduce the dangers of wastes that are not collected for the surrounding environment and human health; and (3) construct new landfills or dumpsites to accommodate extra quantities of CDW. The unit cost to construct a small landfills is approximately 1154 L.E./m3 (165.58 $/m3 ) and this accommodates less than 10,000 ton/year. A medium landfill costs 692 L.E./m3 (99.29 $/m3 ) and this accommodates from 10,000 to 100,000 ton per year. As for a large landfill, it costs 462 L.E./m3 (66.29 $/m3 ) and accommodates more than 100,000 ton/year (BDA Group, 2009). The result of having limited data relevant to the total landfills capacity in Egypt is that the case considers the total occupied capacity from Landfills to the end of 2024 is equal to the current capacity of landfills. The total cost incurred from the state to mitigate the damage resulting from disposal and uncollected waste (TCMDDUCOW) increases significantly each year from L.E. 79.6 million ($11.42 million) to L.E. 3322.3 billion ($476.69 billion) at the end of the simulation run (i.e., considering a time span of 20 years). Fig. 5f displays the effect of activating recycling on the state’s economics by estimating TBRE (total benefits of CDW recycling). Recycling twenty percent from the total waste generated annually would reduce costs (which are paid to reduce the impact of total emissions under study due to landfilling) of L.E. 2.4 billion ($344.36 million) which will be L.E. 112,636.8 billion ($16,161.35 billion) 20 years later. The last step in the procedure of the simulation model development is policy formation after conducting the first four steps described earlier (problem identification, dynamic hypothesis, model formulation, and model validation). Some recommendations
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should be considered to encourage recycling of CDW in Egypt. These recommendations are: • The establishment of recycling centers for construction and demolition wastes. • Developing incentive programs to encourage contractors to recycle their wastes. • Activating strict regulations and laws to prevent illegal dumping. • Forcing contractors to conduct a comprehensive system for managing waste in any construction/demolition project under the supervision of the authorities and impose fines in case of not complying with the system. 6. Conclusions Construction and demolition wastes represent a considerable amount that influences sustainable development aspects with respect to environmental, economic, and social concerns. This paper has presented some developments in a system dynamics model to evaluate the economic and environmental impacts, taking into account two alternatives: recycled wastes and disposed wastes. This research is an empirical study that uses a system dynamics methodology of the CDW management sector by developing a dynamic model capable of studying the behavior of landfill process on both the short and long run and its impacts on the environment and economy. It helps the involved CDW management to examine the interaction among variables affecting of the impacts of landfill and recycling process as an alternative for disposal waste on two major aspects of sustainability, namely the environment and economy. These assessments take into account the different pollutant emissions resulting from disposal in landfills throughout their lifetime, emissions avoided by recycling, and the impact of uncollected waste. The major variables affecting the environmental and economic assessment are identified and the relationships among these variables are described through a causal loop diagram. The interaction among variables is examined through STELLA software. The results from simulation show that waste disposal is not a viable solution to manage CDW. Therefore, regulations should be activated to promote recycling as an alternative for the disposal of CDW. If recycling is conducted on the same quantity of the disposed material in landfills would offer more benefits for environmental and economic aspects. As for the case of Egypt, it would be a substitution for primary raw materials which are estimated to be 12.3 million ton by 2024. This leads to the preservation of natural resources and limited landfills space. Also, recycling would reduce the costs required to mitigate air pollution for L.E. 112,636.8 billion ($16,161.35 billion) over 20 years of simulation time. The simulation results also proved the advantages of recycling technique: (a) it conserves the energy needed for disposing wastes and the upstream; (b) it conserves landfills space; (c) it reduces emissions of GHGs; and (d) it reduces the costs incurred to mitigate air pollution. The research proves that the cost incurred to reduce the dangers to the environment and human health due to uncollected waste and waste landfilling is extremely high. Therefore, recycling of CDW ensures a sustainable environment and economy.
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Appendix 1. Model variables description No.
Abbreviation
Variable name
Unit
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
AACOERE AAGHGERE AANOXEWRE AAPMERE AASO2ERE ACOERRE ACOERE AECLF AGHGEPLF AGHGERE ANOXEWRE ANOXERRE APMERE APMERRE ASERE ASO2ERRE ASO2ERE CLF COERAD COW COELF COERLF DWLF ECUCOW EFCNLF IERLF ELCNLF ESADLF ESRE ESRRE GHGSER GW GWP GHGERAD GHGELF GHGEIR IECEY IRUPCLF IUPCLF LLWLF NOXELF NOXERLF NOXERAD OACOER OAGHGER OANOXERE OAPMER OASO2ERE OSERE PCE PGR PG PMELF PMERLF PMERAD PWNC PWRE PWDL RCOELF REW RGHGELF RNOXELF RPMELF RSO2ELF SEALF SO2ELF SO2RLF SO2ERAD TBRE TCMDDUCOW TRCOELF TDCLFE TDCGHGE
Accumulated Avoided CO Emission by Recycling Accumulated Avoided GHGs Emissions by C&D WASTE Recycling Accumulated Avoided NOX Emission from C&D Waste Recycling Accumulated Avoided PM Emissions by Recycling Accumulated Avoided SO2 Emission by Recycling Avoided CO Emissions Rate by CDW Recycling Avoided CO Emissions by CDW Recycling Accumulated Energy Consumption by Landfilling Accumulated Produced GHGs (CO2 eq) Emissions by landfilling Avoided GHGs Emissions from CDW Recycling Avoided NOX Emissions by CDW Recycling Avoided NOX Emissions Rate by CDW Recycling Avoided PM Emissions by CDW Recycling Avoided PM Emissions Rate by CDW Recycling Accumulated Saved Energy from CDW Recycling Avoided SO2 Emissions Rate by CDW Recycling Avoided SO2 Emissions by CDW Recycling Capacity of Landfills CO Emissions Reducing from Avoided Disposal Collected CDW CO Emissions by landfilling Co Emissions Rate from Landfills Disposed CDW in Landfills Environmental Cost due to Uncollected Waste Extra Funds for the Construction of New Landfills to accommodate excess CDW Increased Energy Rate from Landfilling Economic Losses from Construction New landfills Energy Saving from Avoiding Disposal CDW in landfills Energy Saving of CDW Recycling Energy Saving Rate by CDW Recycling GHGs Saved Emissions Rate Generated Waste Global Warming Potential GHGs Emissions Reducing from Avoiding Disposal GHGs Emissions from Landfilling GHGs Emissions Increasing Rate Increasing Energy Consumption Each Year from Landfills Increasing Rate of Unit private Cost of Landfills Increasing Unit Private Cost of Landfills Land losses from waste landfilled NOX Emissions by landfilling NOX Emissions Rate from landfills NOX Emissions Reducing from Avoided Disposal Overall Avoided CO Emissions by CDW Recycling Overall Avoided GHGs Emissions by CDW Recycling Overall Avoided NOX Emissions by CDW Recycling Overall Avoided PM Emissions by CDW Recycling Overall Avoided SO2 Emissions by CDW Recycling Overall Saved Energy by CDW Recycling Population Census in Egypt (2004) Population Growth Rate Population Growth PM Emissions from landfilling PM Emissions Rate from Landfills PM Emissions Reducing from Avoided Disposal Percentage of CDW that Not Collected Percentage of CDW Recycling Percentage of CDW disposed in Landfills Released CO Emissions from Landfills for the same quantity of waste recycled Recycled CDW Released GHGs Emissions from Landfills for the same quantity of waste recycled Released NOX Emissions from Landfills for the same quantity of waste recycled Released PM Emissions from Landfills for the same quantity of waste recycled Released SO2 Emissions from Landfills for the same quantity of waste recycled Saved Energy from Avoiding Landfilling SO2 Emissions from Landfilling SO2 Emissions Rate from Landfills SO2 Emissions Reduced from Avoiding Disposal Total Benefits of CDW Recycling Total Costs Incurred to Mitigate the Damage from Waste Disposal and Uncollected Waste Total Released CO Emissions from landfills Total Damage costs from Landfills’ Emissions Total Damage cost of GHGs (CO2 eq) Emissions
Ton Ton Ton Ton Ton Ton/ton Ton/year KBTU Ton Ton/year Ton/year Ton/ton Ton/year Ton/ton KBTU Ton/ton Ton/year M3 Ton/year Ton Ton/year Ton/ton Ton L.E. L.E. KBTU/ton L.E. KBTU/year KBTU/year KBTU/ton Ton/ton Ton Ton Ton/year Ton/year Ton/ton KBTU/year % L.E./year M3 /year Ton/year Ton/ton Ton/year Ton Ton Ton Ton Ton KBTU Capita /year Capita/year Ton/year Ton/ton Ton/year /year % % Ton Ton Ton Ton Ton Ton Ton Ton/year Ton/ton Ton L.E. L.E. Ton L.E. L.E.
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a
49
No.
Abbreviation
Variable name
Unit
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98
TDCCOE TDCPM E TDCNOXE TDCSO2E TRNOXELF TOCWLF TRPMELF TRSO2ELF UCOW UDCNOXE UDCSO2E UDCCOE UDCGHGE UECUCOW ULC ULLF UPCLF WCOR WCO WCOR WGPC WG WNC WRE WTLF
Total Damage Cost of CO Emissions Total Damage Cost of PM Emissions Total Damage Cost of NOX Emissions Total Damage Cost of SO2 Emissions Total Released NOX Emissions from landfills Total Occupied Capacity from C&D waste Landfills Total Released PM Emissions from Landfills Total Released SO2 Emissions from Landfills Uncollected CDW Unit Damage Cost of NOX Emissions Unit Damage Cost of SO2 Emissions Unit Damage Cost of CO Emissions Unit Damage cost of GHGs Emissions Unit Environmental Cost due to Uncollected CDW Unit Landfilling Charge Unit Land losses from landfills Unit Private Costs of Landfills Rate of CDW Collecting CDW Collecting Rate of CDW Collecting Waste Generation per capita Waste Generating CDW that is Not Collected CDW Recycling CDW Transported to Landfills
L.E. L.E. L.E. L.E. Ton M3 Ton Ton Ton L.E/ton L.E./ton L.E./ton L.E./ton L.E./ton L.E./ton M3 /ton L.E./M3 Ton/year Ton/year /year Ton/capita/year Ton/year Ton/year Ton/year Ton/year
KBTU is one thousand of British thermal units.
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Resources, Conservation and Recycling journal homepage: www.elsevier.com/locate/resconrec
Environmental and economic impact assessment of construction and demolition waste disposal using system dynamics Mohamed Marzouk ∗ , Shimaa Azab Structural Engineering Department, Faculty of Engineering, Cairo University, Egypt
a r t i c l e
i n f o
Article history: Received 1 March 2013 Received in revised form 8 September 2013 Accepted 27 October 2013 Keywords: Construction and demolition wastes (CDW) Environmental and economic impact assessment Pollutant emissions Waste recycling Global warming potential (GWP) System dynamics modeling
a b s t r a c t Construction and demolition wastes (CDW) have increasingly serious problems in environmental, social, and economic realms. There is no coherent framework for utilization of these wastes which are disposed both legally and illegally. This harms the environment, contributes to the increase of energy consumption, and depletes finite landfills resources. The aim of this paper is to evaluate the impacts of two alternatives for the management of CDW, recycling and disposing. The evaluation is carried out through developing a dynamic model with aid STELLA software by conducting the following steps: (1) quantifying the total cost incurred to mitigate the impacts of CDW landfills and uncollected waste on the environment and human health; (2) quantifying the total avoided emissions and saved energy by recycling waste; (3) estimating total external cost saved by recycling waste and; (4) providing a decision support tool that helps in re-thinking about waste disposal. The proposed evaluation methodology allows activating the stringent regulations that restrict waste disposal and developing incentives to encourage constructors to recycle their wastes. The research findings show that recycling CDW leads to significant reductions in emissions, energy use, global warming potential (GWP), and conserves landfills space when compared to disposal of wastes in landfills. Furthermore, the cost of mitigating the impact of disposal is extremely high. Therefore, it is necessary to recycle construction and demolition wastes. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The construction/demolition industry is considered one of the largest producers of solid wastes globally. The huge amount of construction and demolition wastes (CDW) has been generated from increasing the building of new structures, renovation, rebuilding, repair, demolition works, and infrastructure development projects. Large quantities of construction and demolition wastes (CDW) cause harmful effects on the environment if they are not managed in proper manner. As such, these huge amounts of wastes need to be properly managed. The current situation of waste management in Egypt lies in disposed waste either legally or illegally and there is no coherent framework for making the most of these wastes. It is very important to give priority to the environment in addition to conventional project objectives, such as cost, duration, quality and safety (Liyin et al., 2006). Thinking about waste management from a limited perspective gives rise to some economic concerns. This is because a large amount of money is spent on dumping the waste in landfills and mitigating the effects of dumping on the environment. The environmental problems include: (1) diminishing landfill space due to incremental quantities of these disposed wastes in it; (2) the
∗ Corresponding author. Tel.: +202 35678442. E-mail address: mm [email protected] (M. Marzouk). 0921-3449/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.resconrec.2013.10.015
depleted building materials; (3) the increase in contamination from landfills that lead to serious negative health effects; (4) damage to the environment; and (5) the increase in energy consumption for transportation and manufacturing new materials instead of those materials dumped and which require energy production. The later problem is attributed to the loss of embodied energy of the disposed wastes that can be used to produce new construction materials. It is worth noting that CDW recycling saves the embodied energy in waste materials by the replacement of virgin raw materials with recycled materials (Roussat et al., 2009). Therefore, energy savings are often the driving force behind emissions savings (Choate et al., 2005). CDW are adding to the phenomenon of global warming. Hotter temperatures due to Global Warming Potential (GWP) lead to increased weather extremes including heat waves and worsening of air quality. Epidemiological studies of deaths during the heat waves refer to the fact that a substantial portion of the mortality might be attributed to elevated ozone and particulate levels that occurred during the heat waves (American lung Association, 2004). The California Air Resources Board indicated that the health effects of increasing concentrations of particulate matter and ozone are: 6500 premature deaths, 4000 hospital admissions for respiratory disease, 3000 hospital admissions for cardiovascular disease, 350,000 asthma attacks, 2000 asthma-related emergency room visits, elevated school absences due to respiratory conditions,
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including asthma, and reduced lung function growth rate in children. Sensitive groups, including seniors, people with heart or lung disease, children and infants are the most vulnerable to the harmful effects of air pollution. On the other hand, CDW recycling technique has recently attracted the attention of many researchers due to its economic and environmental benefits. In economic terms, plenty of studies have been conducted on the economic situation of CDW recycling plants such as (Coelho and de Brito, 2013a; Zhao et al., 2010). Both of these studies confirmed the economic feasibility of recycling CDW, but with different results due to the conditions of each study. Coelho and de Brito (2013a) conducted a study on a large-scale recycling plant in Portugal to evaluate the economic viability of the plant for serving a densely populated urban area. This study concluded that despite the absence of regulatory government policy the initial investment required for recycling may be high, but there is a high profit potential for CDW recycling with the return of invested capital in around two years. Zhao et al. (2010) developed a study of the situation in Chongqing in China to assess the economic viability of the implementation of fixed recycling CDW plant facilities and mobile recycling stations and compared it with recycling centers (mobile stations) in the Netherlands to find out successful factors for recycling centers. This study has concluded that fixed and mobile recycling centers with used equipment have higher economy viability than centers with new equipment and that is due to their ability to achieve a higher profit margin in contrast to the second case. Also, the revenue increases owing to the location advantage (e.g. mobile stations) and the recycling cost decreases with the economy of scale (e.g. fixed centers). This study has also suggested the use of economic and political instruments to face the investment risks. Regarding the environmental concerns from recycling plants, several studies have been conducted to evaluate the environmental impacts from CDW recycling plants. Coelho and de Brito (2013b) conducted a study using life cycle assessment of CDW recycling plant with a capacity of 350 ton/h and 60-year operating lifespan. This study has focused on the evaluation of two impacts of recycling plant, namely the primary energy consumption and CO2 eq emissions. The main conclusion of this study is that recycled materials always have significant environmental benefits where the avoided impacts of CO2 eq emissions are always higher than the generated impacts and energy savings exceed the energy consumed during the operating lifespan. F.I.R. (2005) pointed out for several studies conducted to assess the environmental impacts from recycling building materials using life cycle assessment approach from extraction to recovery or disposal of landfills. The first study is presented for assessing the greenhouse gases generated from primary and recycled aggregate. The study has concluded that the recycled aggregate was more environmentally useful than most of primary aggregate. The second study is presented for evaluating environmental impacts of production of 1 ton of concrete through comparing two different scenarios, which are landfilling and recycling. According to this study, the second scenario (recycling) is more environmentally friendly. In order to overcome the above-listed growing problems caused by CDW disposal, it is important to consider a recycling solution. Recycling allows utilizing wastes as raw materials in some other ways. This paper proposes the use of system dynamics methodology to compare between two alternatives of CDW management techniques; recycling and landfill disposal. This model is capable of: (1) measuring the total emissions from the CDW landfilling and associated costs incurred to mitigate the impacts from these emissions; (2) predicting the total damage costs of disposed waste and from uncollected wastes; and (3) quantifying the total avoided emissions and the energy saved by waste recycling. The novelty of this research lies in adopting a system dynamics
approach for all basic variables underlying the evaluation of the two alternatives during the lifetime of landfills. It outperforms previous studies which focus on assessing the two alternatives without taking into account the dynamic nature and relationships between variables. Plenty of studies have been carried out to model CDW management using system dynamics, but they did not take into account the dynamic nature of the CDW disposal and interactions among major variables affecting on evaluation of economic and environmental effects of the CDW disposal as two important aspects of sustainability. This research is an attempt to provide the stakeholders of Egyptian construction sector with an empirical study that considers all variables that influence the CDW. Also, this study helps in mitigating the risks associated with CDW disposal and illustrates the benefits of recycling of construction wastes. 2. Theory and calculations System dynamics is an approach for studying and managing complex feedback systems and is specially created to deal with large-scale and complex systems (Yuan et al., 2012). A system is a group of interacting or interdependent entities forming an integrated whole system dynamics modeling (Cheng, 2012). It was originated by Professor Jay W. Forrester of the Massachusetts Institute of Technology during the mid-1950s (Forrester, 1987). It has been widely used in different applications for understanding different economic, social, business, agricultural, and ecological systems. It deals with internal feedback loops and time delay that affect the behavior of the entire system. It has the ability to understand the relation between the behavior of system over time and its underlying structure and decision rule. Simulation helps explore “what-if” scenarios and policy tests in something that is like a laboratory setting, which causes confidence in particular strategies and policies to increase (Richardson and Otto, 2008). As a result, “system dynamics is often used as a methodology for improving the soundness and effectiveness of the decision-making process. It has become a popular technique for modeling construction project management” (Hao et al., 2007). 3. System dynamics applications in CDW A big number of research works have utilized system dynamics modeling in waste management. Wager and Hilty (2002) have developed system dynamics model for waste management to support the assessment of the flow of materials, energy and costs of regional waste management with regard to their ecological and economic impacts. Chaerul et al. (2008) studied hospital waste management using system dynamics approach to capture its dynamic nature. The behavior of the waste management system depends on several factors including the changing nature of various systemic factors and the feedback generated by a dynamic and continuous interaction. Sliwa (1994) conducted a study on municipal solid waste management in Pueblo using the system dynamics approach. The study has tried to bridge the gap between traditional approaches so as to solve the public administration problems. Lang et al. (2002) developed a systematic methodology for natural and human resources optimization for waste management to achieve sustainable development using system dynamics modeling. Several studies have been published for CDW management (Yuan, 2012; Hao et al., 2007; Rong, 2004; Hsiao et al., 2002; Zhao et al., 2011; Yuan et al., 2011). Yuan (2012) carried out a quantitative study to evaluate the social performance on construction waste management using system dynamics. Many indicators have been used to assess the social impacts of CDW. Hao et al.
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4.1. Problem identification 1) Problem Identification
5) Policy Formulation
4) Model Validation
2) Dynamic Hypothesis
3) Model formulation
Fig. 1. System dynamics model procedure for CDW.
(2007) conducted a study on managing construction and demolition waste. The study showed that system dynamics is able to interrelate the sub-systems and provide better understanding of the dynamic interactions and interdependencies of the key areas of the CDW management process. Rong (2004) used system dynamics approach and analytical hierarchy processing an effort to model sustainable waste management techniques. Hsiao et al. (2002) conducted a study on simulating materials flow of concrete waste from construction and demolition wastes. Also, Zhao et al. (2011) developed a study using system dynamics computer model to evaluate alternatives in CDW recycling centers under different policy and economic environments. Yuan et al. (2011) developed system dynamics model for analyzing the cost-benefit for CDW management. An economic instrument is developed as an effective tool for encouraging or forcing contractors to conduct environmentally friendly construction practices. Previous studies did not take into account the need for assessment of economic and environmental effects of CDW disposal as two important aspects of sustainability. Also, they did not model the different pollutant emissions resulting from disposal in landfills throughout their lifetime from a dynamic point of view. To simulate a system dynamics model, computer support is needed. There are several existing computer packages such as DYNAMO, IThink/STELLA, Matlab, Powersim and Vensim. STELLA is one of the most popular system dynamics software packages which are an effective simulation tool for system dynamics modeling released by High Performance Systems Inc. (HPS, 1997). This software was selected for supporting the analysis in this study. The basic building blocks of STELLA are stock; flow; converter; and connector. A stock variable (represented by rectangles) is a noun and represents something that accumulates. A flow (represented by valves) is an activity that changes the magnitude of a stock by filling and draining. The converter (represented by circle) can be used to modify an activity for its ability to define external inputs to the model. The connector (represented by simple arrow) is able to connect model elements (Shiflet and Shiflet, 2006; Zhao et al., 2011). 4. Development of system dynamics model The objective of this research is to provide a dynamic model by conducting an empirical study using system dynamics methodology to capture the dynamic nature of two alternatives for CDW management which are waste recycling and disposal. The proposed model is able to simulate the long-term behavior of each alternative in two main aspects of cost and environmental impacts. To achieve this objective, a simulation model is developed by following the procedure shown in Fig. 1. The description of the proposed procedure is detailed in below sub-sections.
To simulate the long-term impacts of CDW recycling and landfilling on the aspects of cost and environment, all essential variables that affect the system are considered. The variables rates used in the model have been collected from various published literature and through surveying the Egyptian market. The time horizon should be long enough to show the impact of CDW recycling and disposal and describe its symptoms. Therefore, it should extend far back in history. Also, it should extend far enough into the future to capture the delayed and indirect effect of potential policies (Sterman 2000). Rong (2004) recommended the service life of the waste treatment/disposal facility that is usually 20–30 years. Therefore, the time horizon in the proposed system dynamics model is selected to be 20 years (i.e., from 2004 to 2024).
4.2. Dynamic hypothesis Evaluating economic and environmental impacts of CDW management alternatives on the long-run requires examining the major variables effect on the assessment. This is done by using a tool that is capable of visualizing relationships of variables and feedback effects of the system. The structure of the system dynamics model is portrayed by a causal loop diagram, which is formulated by VENSIM software as shown in Fig. 2. The developed causal loop diagram comprises eight loops (R1, R2, R3, R4, R5, R6, R7, and R8) in total; all loops are reinforcing (positive loops). The interactions among different loops decide the system’s final behavior. Feedback loop R1 shows the relationship between CDW recycling and energy consumption saving where CDW recycling leads to an increase in energy consumption savings. On the other hand, when savings in energy consumption from recycling increase, it leads to conduct more recycling. This relationship, as a natural result of the recycling process, reduces the need for the upstream phase. When using recycled materials, this replaces part of the inputs that would be produced from raw material, skipping some stages of the production chain or replaces some stages which lead to less energy-consumption (Pimenteira et al., 2004). Feedback loop R2 shows that the recycling process helps in reducing emissions polluting the air ambient (e.g. NOX, SO2, PM, and CO emissions) which leads to better human health. As a result, all emissions polluting the air will be reduced when more recycling takes place instead of landfilling, where the total reductions in emissions is equal to the avoided emissions from landfilling plus the avoided emissions from reducing the need for the upstream phase. Energy savings are often the driving force behind emissions savings (Choate et al., 2005). Consequently, the amount of recycled waste will be increased due to the total reduction in pollutants emissions. By referring to feedback loop R3, it can be observed that the amount of greenhouse gases (GHGs) emissions is reduced by increasing recycling. This in turn leads to reducing the chance of causing global warming potential. Consequently, the amount of recycled waste will be increased due to the reduction in the GWP phenomenon. The causal loop relationships in loop 4 are the same as in loop R2; the only difference is the effect of GHGs emissions instead of emissions polluting the air. Some of the causal loop relationships in loop R5 are the same as in loop R4; the difference is that the total reduction in emissions from landfills leads to an increase in the total saved damage cost through mitigating the effect of these emissions on environment, air ambient, as well as they eliminate the negative effect on human health. This has positive effects on economic gains. Consequently, if economic gains are high, then, contractors are keen to have incentives of having more recycling (Yuan et al., 2011). Economic instrument is perceived as
44
M. Marzouk, S. Azab / Resources, Conservation and Recycling 82 (2014) 41–49
Waste Generation Per Capita
Percentage of C&D Waste that Not Collected
+ -
+ Waste Collection + + Uncollected waste + Population Census
+ + C&D Waste Generation
Occupation Of Landfill Space +
+ Waste Disposal +
Existing landfill capacity
Emissions polluting the air
+ Extra Funds for New Landfills
Total Damage Costs From Emissions of Landfills + +
Energy consumption saving + + Greenhouse gas emissions -
Unit landfill Charge
+
-Total Reductions in Emissions By Recycling
+
R1 R3
Population Growth Rate
+ Damage Costs Of Emissions +
R4
+ Recycling Ratio Unit Environmental cost due to uncollected waste
Private Costs Of Unit Landfills
Collection Rate
+
+
Global warming
R2
+
+
R5
+ ECONOMIC GAINS
+
R6
Waste Recycling
-
+
R8
+
+
Total Cost from disposal & uncollected waste R7
+
Unit Damage Cost Of Air Emissions
Total damage cost Avoided By Recycling
Damage Costs from GHG Emissions +
+ + Environmental Cost due to Uncollected Waste
Unit Damage Cost of GHG Emissions.
Fig. 2. Causal loop structure of the proposed model.
an effective tool for encouraging or forcing contractors to adopt environmentally friendly construction practices. Some of the causal loop relationships in loop 6 are the same as in loop R5; the only difference is the effect of emissions polluting the air, not the effect of GHGs emissions. In feedback loop R7; it can be observed that conducting more recycling for CWD leads to the reduction of the emissions polluting the air. The total damage costs from emissions of landfills are consequently reduced since CDW in landfill is less. Also, the total costs from disposal and uncollected waste are reduced. As a result, the economic gains will be increased by conducting more recycling and high economic gains will lead to further recycling. Feedback loop R8 is the same loop R7 except that the effect of emissions polluting the air is replaced by the effect of GHGs emissions. 4.3. Model formulation Based on the causal loop diagram, all the key variables that affect the choice of CDW management techniques alternatives are identified. The conceptual causal loop diagram is converted to a quantitative model to facilitate the running of the model. To this end, the causal loop diagram is converted into a stock-flow diagram using STELLA software. Fig. 3 depicts stock-flow diagram of the model. Detailed descriptions of the model variables are included in Appendix 1. 4.4. Model validation Building confidence in the model is achieved through conducting some tests after identifying and defining all variables and functions (Sterman 2000). This ensures the accuracy of the model for reflecting the real-world in a meaningful way (Richardson and Pugh, 1981). Qudrat-Ullah and Seong (2010) listed five tests that are used for structural validation of a system dynamics model. The
validation tests are conducted in the developed model as described below. 4.4.1. Boundary-adequacy test This test is concerned with whether the level of detailed variables contained in the model is appropriate to the research purpose or not. Meanwhile, it assures that the model includes all relevant structure relationships and parameters by examining all the variables that have been embodied in stock-flow diagram. After examining all variables in the system dynamics model, it was found that each of these variables is fundamental for research purpose so as to evaluate the environmental and economic performances associated with the disposal and recycle of CDW. 4.4.2. Structure verification test The purpose of this test is to check whether the model structure is consistent with relevant descriptive knowledge of the system being modeled. The structural verification is important in the overall validation process (Qudrat-Ullah and Seong, 2010). The information included in the structure and all cause-and-effect chains of the causal loop diagram (shown in Fig. 2) is based on various literatures in this domain. As such, the structure of that model is logical and closely represent the real life system. 4.4.3. Dimension consistency test This test ensures the consistency of variable dimensions of each mathematical equation in the model. STELLA software has the possibility of dimension checking after defining the measurement units of all the variables. Consequently, the model has been validated for dimensional consistency. The variable “AAPMERE” (shown in Fig. 4), for instance, is defined using Eq. (1): AAPMERE (t) = AAPMERE (t − dt) + (APMERE) ∗ dt
(1)
This equation is used to calculate the total avoided PM Emissions through construction and demolition waste recycling. It is
M. Marzouk, S. Azab / Resources, Conservation and Recycling 82 (2014) 41–49
45
Fig. 3. A stock-flow diagram for assessing the economic and environmental impacts of CDW.
Equ
AAPMERE (t)
=
AAPMERE (t - dt)
+
Dim
Ton
=
Ton
+
(APMERE) * dt
Ton* Ton/Ton
Fig. 4. Dimension consistency test on one of the model variables.
Table 1 Population growth rate in Egypt 2000–2025 (Awad and Zohary, 2005). Period
2000–2005
2005–2010
2010–2015
2015–2020
2020–2025
Population growth rate (%)
1.91
1.83
1.67
1.46
1.28
worth noting that the variable dimensions on the left-hand side are consistent with the variables dimensions on the right-hand side. 4.4.4. Parameter verification test The purpose of this test is to check whether the parameters in the model correspond conceptually and numerically to real life. The parameter values of the proposed model are taken from real cases conducted in literature. For illustration, Tables 1 and 2 include some of the parameters, their values and the source. 4.4.5. Extreme conditions test This test examines the behavior of the model by assigning extreme values for the model variables. Extreme values for specific variables are compared with the reference behavior of the principled model. To clarify the purpose of the test, the variable ULC (Unit Landfilling Charge) is taken as an example for the test. The impact of ULC on REW (the quantity of recycled from CDW) over time is examined by changing the value of ULC from L.E. 6.11 ($0.88) to L.E. 58 ($8.32) and monitoring how the value of REW influences model behavior. The findings show that in case of higher landfill charge,
contractors’ incentive increases to conduct more CDW recycling which increases REW compared to the initial value of ULC (see Fig. 5a). In case of low unit landfill charge (L.E.6.11), most wastes are disposed either legally or illegally. This result reflects the natural attitude of contractors, where costs represent high priority with the absence of incentives for recycling and/or contract clauses that force contractors to recycle CDW. Table 2 Model variables and their respective values. Model variables
Values
Source
NOX emissions from recycling 1 ton from CDW GWP (CO2 eq) emissions from recycling 1 ton from CDW Energy used for recycling 1 ton from CDW GWP emissions from processing 1 ton of CDW in a Landfill Energy used for Processing 1 ton of CDW in a landfill Unit land losses from landfills space by CDW landfilling
−2 ton −600 Ibs
Levis (2008)
−9000 kBtu 200 Ibs 600 kBtu 0.6 M3 /ton
F.I.R. (2005)
46
M. Marzouk, S. Azab / Resources, Conservation and Recycling 82 (2014) 41–49 4.50E+07
5.00E+07
4.00E+07
Unit Landfilling Charge (ULC)=6.11
4.50E+07
3.50E+07
Unit Landfilling Charge (ULC)=58
4.00E+07 3.50E+07
Tons
3.00E+07
Tons
2.50E+07 2.00E+07
2.50E+07
1.50E+07
1.00E+07
1.00E+07
5.00E+06
5.00E+06 0.00E+00
0.00E+00 0
1
2
3
4
5
6
7
8
0
9 10 11 12 13 14 15 16 17 18 19 20
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
Years
b) Quantities of recycled, landfilled and uncollected CDW over simulation time
a) Unit landfilling charge impact on the quantity of recycled from CDW
4.50E+07
3.50E+07 3.00E+07 2.50E+07 2.00E+07 1.50E+07 1.00E+07 5.00E+06
2.00E+12 Kilo Brish Thermal Units (KBTU)
Released GHGs Emissions from Landfills for the same quanty of waste recycled (RGHGELF) Overall Avoided GHGs Emissions by CDW Recycling (OAGHGER)
4.00E+07
Tons CO2eq
3.00E+07
2.00E+07
1.50E+07
-5.00E+06
Recycled CDW (REW) Disposed CDW in Landfill (DWLF) Uncollected CDW (UCOW)
1.80E+12
Saved Energy from Avoiding Landfilling (SEALF)
1.60E+12
Overall Saved Energy by Recycling (OSERE)
1.40E+12 1.20E+12 1.00E+12 8.00E+11 6.00E+11 4.00E+11 2.00E+11 0.00E+00
0.00E+00 0
1
2
3
4
5
6
7
8
0
9 10 11 12 13 14 15 16 17 18 19 20
1
2
3
4
5
6
7
Years d)
c) Effect of recycling and landfills on global warming potential
ed Waste (TCMDDUCOW)
3.50E+12
9 10 11 12 13 14 15 16 17 18 19 20
Amount of Consumed Energy and Saved Energy over simulation time
1.20E+14
Total Costs incurred to Migate the Damage from Disposal and Uncollect
3.00E+12
8
Years
Total Benefits of CDW Recycling (TBRE)
1.00E+14
2.50E+12
8.00E+13
L.E.
L.E.
2.00E+12 1.50E+12
6.00E+13 4.00E+13
1.00E+12
2.00E+13
5.00E+11 0.00E+00
0.00E+00 0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
e) Economic burden from waste disposal over simulation time
f) Economic benefits of waste recycling
Fig. 5. System dynamics model outputs.
5. Results and discussion After conducting the validation tests, the model is simulated over a total period of 20 years, which corresponds to the total life time of CDW landfills. In case of enforcement methodology to benefit from construction and demolition waste by recycling instead of disposal (without implementing government policies), the proportion of recycled materials is influenced by contractors’ perceptions where cost has higher priority than environment. Thus, the percentage of recycled material is influenced by the unit landfill charge. Fig. 5b depicts the projection of the amount of CDW that is: (1) disposed in landfills; (2) uncollected; and (3) recycled. It should be noted that the amount of waste recycled (REW) in the first year is only 20% of the total collected waste that is approximately 32 thousand ton and over the simulated time (20 years). A total of 12.3 million ton of materials will be recycled from a huge amount of CDW that is generated annually (4.5 million tons/year). This quantity is considered very little compared to the quantities dumped in landfills annually and uncollected wastes. The total disposed waste in landfills (DWLF) over a lifetime is 49.2 million
ton and this represents the largest amount of waste, which leads to diminishing landfill space rapidly and causes ambient air pollution that is so dangerous to human health. The amount of uncollected wastes (UCOW) is 35.2 million ton over a simulation time which is much greater than the amount of recycled wastes. This is attributed to the absence of enforcing strict laws and regulations that prevent illegal dumping for the preservation the environment. Fig. 5c depicts the comparison between the simulation of the effect of GHGs emissions released from landfills and the impact of the recycling process on global warming potential (GWP). The figure shows the effect of disposed waste on GWP through the amount of GHGs emissions (CO2 eq) released from landfills (RGHGELF) and the effect of the recycling process by estimating the overall avoided GHGs emissions by CDW Recycling (OAGHGER) that is equal to the total avoided emissions from landfilling and the avoided emissions from eliminating the need for the upstream phase. It should be noted that GHGs emissions (CO2 eq) released from landfills increases significantly during its operations and even after closure. This leads to an increase in GWP which increases
M. Marzouk, S. Azab / Resources, Conservation and Recycling 82 (2014) 41–49
emissions in the atmosphere from 228.52 ton in the first run on simulation to 10.45 million ton over 20 years. In contrast, in waste recycling processes, the concentration of GHGs emissions gradually decreases (avoided emissions increase) over time and this leads to a reduction in the chance of global warming from 914 ton in first year of simulation to 41.8 million ton at the end of simulation (2024). Fig. 5d shows the effect of disposed waste in landfills and recycling process in energy consumption. The relationship between SEALF (Saved Energy from Avoiding LandFills) and the lifetime of landfills is depicted in the figure. It shows that the energy consumption by landfilling for the same recycled quantity ranges from 1.37 million KBTU (Kilo British Thermal Units) to 62.69 billion KBTU at the end of the simulation run. These huge losses from energy consumption can be maintained by conducting a recycling process on CDW. The results from simulation indicate that by conducting recycling on the same quantity, OSERE (Overall Saved Energy due to Recycling) ranges from 21.94 million KBTU to 1003 billion KBTU. It is a fact that recycling reduces the need for the upstream phase. Also, when materials are recycled, this replaces part of the inputs that would be produced from raw material, skipping some stages of the production chain or replacing some stages which lead to less energy-consumption. Fig. 5e depicts the impact of not handling the CDW in an appropriate manner on the economy. A large amount of money will be incurred by the government to: (1) eliminate the damage that results from landfills emissions whether in air ambient or on human health; (2) reduce the dangers of wastes that are not collected for the surrounding environment and human health; and (3) construct new landfills or dumpsites to accommodate extra quantities of CDW. The unit cost to construct a small landfills is approximately 1154 L.E./m3 (165.58 $/m3 ) and this accommodates less than 10,000 ton/year. A medium landfill costs 692 L.E./m3 (99.29 $/m3 ) and this accommodates from 10,000 to 100,000 ton per year. As for a large landfill, it costs 462 L.E./m3 (66.29 $/m3 ) and accommodates more than 100,000 ton/year (BDA Group, 2009). The result of having limited data relevant to the total landfills capacity in Egypt is that the case considers the total occupied capacity from Landfills to the end of 2024 is equal to the current capacity of landfills. The total cost incurred from the state to mitigate the damage resulting from disposal and uncollected waste (TCMDDUCOW) increases significantly each year from L.E. 79.6 million ($11.42 million) to L.E. 3322.3 billion ($476.69 billion) at the end of the simulation run (i.e., considering a time span of 20 years). Fig. 5f displays the effect of activating recycling on the state’s economics by estimating TBRE (total benefits of CDW recycling). Recycling twenty percent from the total waste generated annually would reduce costs (which are paid to reduce the impact of total emissions under study due to landfilling) of L.E. 2.4 billion ($344.36 million) which will be L.E. 112,636.8 billion ($16,161.35 billion) 20 years later. The last step in the procedure of the simulation model development is policy formation after conducting the first four steps described earlier (problem identification, dynamic hypothesis, model formulation, and model validation). Some recommendations
47
should be considered to encourage recycling of CDW in Egypt. These recommendations are: • The establishment of recycling centers for construction and demolition wastes. • Developing incentive programs to encourage contractors to recycle their wastes. • Activating strict regulations and laws to prevent illegal dumping. • Forcing contractors to conduct a comprehensive system for managing waste in any construction/demolition project under the supervision of the authorities and impose fines in case of not complying with the system. 6. Conclusions Construction and demolition wastes represent a considerable amount that influences sustainable development aspects with respect to environmental, economic, and social concerns. This paper has presented some developments in a system dynamics model to evaluate the economic and environmental impacts, taking into account two alternatives: recycled wastes and disposed wastes. This research is an empirical study that uses a system dynamics methodology of the CDW management sector by developing a dynamic model capable of studying the behavior of landfill process on both the short and long run and its impacts on the environment and economy. It helps the involved CDW management to examine the interaction among variables affecting of the impacts of landfill and recycling process as an alternative for disposal waste on two major aspects of sustainability, namely the environment and economy. These assessments take into account the different pollutant emissions resulting from disposal in landfills throughout their lifetime, emissions avoided by recycling, and the impact of uncollected waste. The major variables affecting the environmental and economic assessment are identified and the relationships among these variables are described through a causal loop diagram. The interaction among variables is examined through STELLA software. The results from simulation show that waste disposal is not a viable solution to manage CDW. Therefore, regulations should be activated to promote recycling as an alternative for the disposal of CDW. If recycling is conducted on the same quantity of the disposed material in landfills would offer more benefits for environmental and economic aspects. As for the case of Egypt, it would be a substitution for primary raw materials which are estimated to be 12.3 million ton by 2024. This leads to the preservation of natural resources and limited landfills space. Also, recycling would reduce the costs required to mitigate air pollution for L.E. 112,636.8 billion ($16,161.35 billion) over 20 years of simulation time. The simulation results also proved the advantages of recycling technique: (a) it conserves the energy needed for disposing wastes and the upstream; (b) it conserves landfills space; (c) it reduces emissions of GHGs; and (d) it reduces the costs incurred to mitigate air pollution. The research proves that the cost incurred to reduce the dangers to the environment and human health due to uncollected waste and waste landfilling is extremely high. Therefore, recycling of CDW ensures a sustainable environment and economy.
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Appendix 1. Model variables description No.
Abbreviation
Variable name
Unit
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
AACOERE AAGHGERE AANOXEWRE AAPMERE AASO2ERE ACOERRE ACOERE AECLF AGHGEPLF AGHGERE ANOXEWRE ANOXERRE APMERE APMERRE ASERE ASO2ERRE ASO2ERE CLF COERAD COW COELF COERLF DWLF ECUCOW EFCNLF IERLF ELCNLF ESADLF ESRE ESRRE GHGSER GW GWP GHGERAD GHGELF GHGEIR IECEY IRUPCLF IUPCLF LLWLF NOXELF NOXERLF NOXERAD OACOER OAGHGER OANOXERE OAPMER OASO2ERE OSERE PCE PGR PG PMELF PMERLF PMERAD PWNC PWRE PWDL RCOELF REW RGHGELF RNOXELF RPMELF RSO2ELF SEALF SO2ELF SO2RLF SO2ERAD TBRE TCMDDUCOW TRCOELF TDCLFE TDCGHGE
Accumulated Avoided CO Emission by Recycling Accumulated Avoided GHGs Emissions by C&D WASTE Recycling Accumulated Avoided NOX Emission from C&D Waste Recycling Accumulated Avoided PM Emissions by Recycling Accumulated Avoided SO2 Emission by Recycling Avoided CO Emissions Rate by CDW Recycling Avoided CO Emissions by CDW Recycling Accumulated Energy Consumption by Landfilling Accumulated Produced GHGs (CO2 eq) Emissions by landfilling Avoided GHGs Emissions from CDW Recycling Avoided NOX Emissions by CDW Recycling Avoided NOX Emissions Rate by CDW Recycling Avoided PM Emissions by CDW Recycling Avoided PM Emissions Rate by CDW Recycling Accumulated Saved Energy from CDW Recycling Avoided SO2 Emissions Rate by CDW Recycling Avoided SO2 Emissions by CDW Recycling Capacity of Landfills CO Emissions Reducing from Avoided Disposal Collected CDW CO Emissions by landfilling Co Emissions Rate from Landfills Disposed CDW in Landfills Environmental Cost due to Uncollected Waste Extra Funds for the Construction of New Landfills to accommodate excess CDW Increased Energy Rate from Landfilling Economic Losses from Construction New landfills Energy Saving from Avoiding Disposal CDW in landfills Energy Saving of CDW Recycling Energy Saving Rate by CDW Recycling GHGs Saved Emissions Rate Generated Waste Global Warming Potential GHGs Emissions Reducing from Avoiding Disposal GHGs Emissions from Landfilling GHGs Emissions Increasing Rate Increasing Energy Consumption Each Year from Landfills Increasing Rate of Unit private Cost of Landfills Increasing Unit Private Cost of Landfills Land losses from waste landfilled NOX Emissions by landfilling NOX Emissions Rate from landfills NOX Emissions Reducing from Avoided Disposal Overall Avoided CO Emissions by CDW Recycling Overall Avoided GHGs Emissions by CDW Recycling Overall Avoided NOX Emissions by CDW Recycling Overall Avoided PM Emissions by CDW Recycling Overall Avoided SO2 Emissions by CDW Recycling Overall Saved Energy by CDW Recycling Population Census in Egypt (2004) Population Growth Rate Population Growth PM Emissions from landfilling PM Emissions Rate from Landfills PM Emissions Reducing from Avoided Disposal Percentage of CDW that Not Collected Percentage of CDW Recycling Percentage of CDW disposed in Landfills Released CO Emissions from Landfills for the same quantity of waste recycled Recycled CDW Released GHGs Emissions from Landfills for the same quantity of waste recycled Released NOX Emissions from Landfills for the same quantity of waste recycled Released PM Emissions from Landfills for the same quantity of waste recycled Released SO2 Emissions from Landfills for the same quantity of waste recycled Saved Energy from Avoiding Landfilling SO2 Emissions from Landfilling SO2 Emissions Rate from Landfills SO2 Emissions Reduced from Avoiding Disposal Total Benefits of CDW Recycling Total Costs Incurred to Mitigate the Damage from Waste Disposal and Uncollected Waste Total Released CO Emissions from landfills Total Damage costs from Landfills’ Emissions Total Damage cost of GHGs (CO2 eq) Emissions
Ton Ton Ton Ton Ton Ton/ton Ton/year KBTU Ton Ton/year Ton/year Ton/ton Ton/year Ton/ton KBTU Ton/ton Ton/year M3 Ton/year Ton Ton/year Ton/ton Ton L.E. L.E. KBTU/ton L.E. KBTU/year KBTU/year KBTU/ton Ton/ton Ton Ton Ton/year Ton/year Ton/ton KBTU/year % L.E./year M3 /year Ton/year Ton/ton Ton/year Ton Ton Ton Ton Ton KBTU Capita /year Capita/year Ton/year Ton/ton Ton/year /year % % Ton Ton Ton Ton Ton Ton Ton Ton/year Ton/ton Ton L.E. L.E. Ton L.E. L.E.
M. Marzouk, S. Azab / Resources, Conservation and Recycling 82 (2014) 41–49
a
49
No.
Abbreviation
Variable name
Unit
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98
TDCCOE TDCPM E TDCNOXE TDCSO2E TRNOXELF TOCWLF TRPMELF TRSO2ELF UCOW UDCNOXE UDCSO2E UDCCOE UDCGHGE UECUCOW ULC ULLF UPCLF WCOR WCO WCOR WGPC WG WNC WRE WTLF
Total Damage Cost of CO Emissions Total Damage Cost of PM Emissions Total Damage Cost of NOX Emissions Total Damage Cost of SO2 Emissions Total Released NOX Emissions from landfills Total Occupied Capacity from C&D waste Landfills Total Released PM Emissions from Landfills Total Released SO2 Emissions from Landfills Uncollected CDW Unit Damage Cost of NOX Emissions Unit Damage Cost of SO2 Emissions Unit Damage Cost of CO Emissions Unit Damage cost of GHGs Emissions Unit Environmental Cost due to Uncollected CDW Unit Landfilling Charge Unit Land losses from landfills Unit Private Costs of Landfills Rate of CDW Collecting CDW Collecting Rate of CDW Collecting Waste Generation per capita Waste Generating CDW that is Not Collected CDW Recycling CDW Transported to Landfills
L.E. L.E. L.E. L.E. Ton M3 Ton Ton Ton L.E/ton L.E./ton L.E./ton L.E./ton L.E./ton L.E./ton M3 /ton L.E./M3 Ton/year Ton/year /year Ton/capita/year Ton/year Ton/year Ton/year Ton/year
KBTU is one thousand of British thermal units.
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